Finding k-cuts within twice the optimal
SFCS '91 Proceedings of the 32nd annual symposium on Foundations of computer science
A multilevel algorithm for partitioning graphs
Supercomputing '95 Proceedings of the 1995 ACM/IEEE conference on Supercomputing
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Mesh Partitioning: A Multilevel Balancing and Refinement Algorithm
SIAM Journal on Scientific Computing
Solving the mesh-partitioning problem with an ant-colony algorithm
Parallel Computing - Special issue: Parallel and nature-inspired computational paradigms and applications
A Combined Evolutionary Search and Multilevel Optimisation Approach to Graph-Partitioning
Journal of Global Optimization
Polynomial algorithm for the k-cut problem
SFCS '88 Proceedings of the 29th Annual Symposium on Foundations of Computer Science
Multilevel heuristic algorithm for graph partitioning
EvoWorkshops'03 Proceedings of the 2003 international conference on Applications of evolutionary computing
Multi-a(ge)nt Graph Patrolling and Partitioning
WI-IAT '09 Proceedings of the 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology - Volume 02
Reconstruction of networks from their betweenness centrality
Evo'08 Proceedings of the 2008 conference on Applications of evolutionary computing
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The k-cut problem is an NP-complete problem which consists of finding a partition of a graph into k balanced parts such that the number of cut edges is minimized. Different algorithms have been proposed for this problem based on heuristic, geometrical and evolutionary methods. In this paper we present a new simple multiagent algorithm, ants, and we test its performance with standard graph benchmarks. The results show that this method can outperform several current methods while it is very simple to implement.